{"id":"W6905941345","doi":"10.15468/dl.z99ehc","title":"Occurrence Download","year":2019,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Real world data; Order (exchange)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008206532,0.00220426,0.001812667,0.005775289,0.001147728,0.003763625,0.002629572,0.001992339,0.2640702],"category_scores_gemma":[0.006276159,0.0009922453,0.001703042,0.009349802,0.0003950768,0.003727075,0.003855424,0.002266025,0.3955912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001302446,"about_ca_system_score_gemma":0.002203505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01364057,"about_ca_topic_score_gemma":0.02432606,"domain_scores_codex":[0.9987918,0.0001342619,0.0001610725,0.0004434402,0.0002650531,0.0002044606],"domain_scores_gemma":[0.9974608,0.000642677,0.0001867923,0.00076299,0.000612954,0.0003337252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003822571,0.00001276901,0.0003807212,0.0005199455,0.00001406083,0.00002098509,0.00002591295,0.00009365402,0.0001100594,0.0004087865,0.9954847,0.002890212],"study_design_scores_gemma":[0.00005236562,0.00001120726,0.001285616,0.0001564636,0.0000130159,0.00004690735,0.00008919805,0.0002110711,0.0001811466,0.001045899,0.9968887,0.0000184938],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007257306,0.00006209522,0.0001193592,0.0000774452,0.00003894549,0.00001114747,0.9957979,0.001955342,0.001865232],"genre_scores_gemma":[0.0002670835,0.00007298203,0.0004417165,0.0001020574,0.00001134886,0.00005149826,0.9969605,0.0005718636,0.001520862],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7359298,"threshold_uncertainty_score":0.8834029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}